CN109347769A - The channel joint estimation method of two-way multiple-input and multiple-output relay system - Google Patents
The channel joint estimation method of two-way multiple-input and multiple-output relay system Download PDFInfo
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- CN109347769A CN109347769A CN201811144605.2A CN201811144605A CN109347769A CN 109347769 A CN109347769 A CN 109347769A CN 201811144605 A CN201811144605 A CN 201811144605A CN 109347769 A CN109347769 A CN 109347769A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L25/00—Baseband systems
- H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
- H04L25/0202—Channel estimation
- H04L25/024—Channel estimation channel estimation algorithms
- H04L25/0242—Channel estimation channel estimation algorithms using matrix methods
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- H—ELECTRICITY
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- H04B7/00—Radio transmission systems, i.e. using radiation field
- H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
- H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
- H04B7/0413—MIMO systems
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B7/00—Radio transmission systems, i.e. using radiation field
- H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
- H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
- H04B7/0413—MIMO systems
- H04B7/0417—Feedback systems
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- H—ELECTRICITY
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- H04L25/00—Baseband systems
- H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
- H04L25/0202—Channel estimation
- H04L25/0204—Channel estimation of multiple channels
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Abstract
The present invention relates to the channel joint estimation methods of two-way multiple-input and multiple-output relay system.Precision of channel estimation with higher and lower computation complexity, can quickly and accurately realize channel estimation.Implementation step are as follows: the 1) foundation of two-way multiple-input and multiple-output relay system model；2) design of channel training signals；3) relay encodes received signal and is sent to user；4) user terminal constructs TUCK-2 tensor model to received signal.5) the iterative fitting algorithm of low complex degree is designed to realize the Combined estimator of channel matrix.The low advantage of of the invention channel estimation methods tool precision height and computation complexity, in addition, the present invention also can effectively estimate channel even if channel relevancy enhances.
Description
Technical field
The present invention relates to wireless communication technology field, in particular to the channel of two-way multiple-input and multiple-output relay system is combined
Estimation method
Background technique
Multiple-input and multiple-output (MIMO) relay system reduces path loss, the expansion network coverage, raising energy due to having
The advantages that efficiency and be concerned.MIMO relay system can be provided additional by the space diversity using more antennas
Power simultaneously saves band resource.If the channel state information (CSI) of known MIMO relay system, so that it may maximize entire logical
The energy and spectrum efficiency of letter system.However, in actual relay communications system, CSI be it is unknown, need to be estimated.
In order to preferably optimize entire relay communications system, known information source-relaying and relaying-stay of two nights link channel are needed
Matrix.Traditional mimo channel estimation method can be applied to MIMO relay system, such as be based on the channel of least square (LS)
Estimation method.Tradition carries out channel estimation based on the channel estimation methods needs of LS on relay node.However, relay node
Usually there is limited computing capability, be difficult to complete the task of channel estimation.Currently, having existed for much about unidirectional
The work of MIMO relay communications system channel estimation.In bidirectional relay system, two information sources or user pass through relay node
Assist the exchange to realize information.Compared to unidirectional MIMO relay system, two-way MIMO relay system is imitated with higher frequency spectrum
Rate, therefore receive more and more attention in recent years.However compared with unidirectional MIMO relay system, two-way MIMO relay system
Channel estimation problems it is increasingly complex, significant challenge is how all CSI to be obtained at destination node or user.It is right
In two-way MIMO relay system, more commonly used channel estimation methods have superposition channel training and two stages channel estimation method.So
And superposition channel training algorithm estimated accuracy is poor, there are error propagation phenomenons for two stages channel estimation method.
TUCK-2 model has identifiability advantage, compared with existing channel estimation methods, required channel training sequence compared with
It is few.In addition, designed fitting algorithm has lower computation complexity, channel estimation can be rapidly realized.
Summary of the invention
Goal of the invention: in view of the deficiencies of the prior art, the present invention proposes channel a kind of in two-way MIMO relay system joints
Estimation method, rapidly to estimate CSI all in system.
Technical solution: the channel joint estimation method of two-way multiple-input and multiple-output relay system of the present invention includes:
The foundation of two-way multiple-input and multiple-output relay system model；
The design of channel training signals；
Relay encodes received signal and is sent to user；
User terminal constructs TUCK-2 tensor model to received signal；
The iterative fitting algorithm of low complex degree is designed to realize the Combined estimator of channel matrix.
Further, the foundation of the two-way multiple-input and multiple-output relay system model, specifically includes:
WithIt respectively indicates user 1 and arrives relay node channel square to relay node and user 2
Battle array.
WithRelay node is respectively indicated to user 1 and relay node to the channel of user 2
Matrix.
Design assumes that all channels are all quasi-static bulk nanometer materials, and considers time division duplex (TDD) mode, that is, hasWith
Further, the design of channel training signals, comprising:
During l (l=1 ..., L) height, orthogonal channel training sequenceWithRespectively by
User 1 and user 2 are sent to relaying.
The signal of relay reception are as follows:
Further, relay encodes received signal and is sent to user, comprising:
Relaying is to the signal X receivedlIt is encoded, and it is forwarded to user 1 and user 2 respectively.User 1 and use
2 received signal of familyWithIt respectively indicates are as follows:
Further, user terminal constructs TUCK-2 tensor model to received signal, comprising:
In user terminal, to receive the both sides of signal respectively and meanwhile multiplied byWithIt can obtain:
It can be modeled as having noisy TUCK-2 tensor model, the scalar form of the TUCK-2 model are as follows:
According to TUCK-2 resolution characteristic, following four compact form can be obtained:
Further, the iterative fitting algorithm of low complex degree is designed to realize the Combined estimator of channel matrix, comprising:
Step (1) is usedWithIt is rightWithMultiply after progress, the LS estimation of two Kronecker products can be obtainedWith
Step (2): initializationAnd set it=0；
Step (3): titi=+1；
Step (4): to m=1 ..., M and n2=1 ..., N is calculatedIt is as follows:
Step (5): to mi=1 ..., MiAnd n1=1 ..., N is calculatedIt is as follows:
Step (6): (3) to (5) are repeated until convergence；
Step (7): it is fuzzy to eliminate scale.
The utility model has the advantages that compared with prior art, major advantage is: it is all that the present invention can estimate system in user terminal
CSI, alleviate the burden of relaying；Even if channel relevancy enhances, which also can effectively estimate channel；The algorithm is not
The pseudoinverse of calculating matrix in each iteration, precision of channel estimation with higher and lower computation complexity are needed, it can be fast
Speed accurately realizes channel estimation.
Detailed description of the invention
Fig. 1 is channel estimation methods flow chart of the invention；
Fig. 2 is two-way MIMO relay system structural schematic diagram of the invention；
Fig. 3 is channel estimating performance figure of the present invention at different channels training sequence number L；
Fig. 4 is channel estimating performance figure of the present invention at different channels training sequence length T；
Fig. 5 is channel estimating performance figure of the present invention at different N；
Fig. 6 compares figure in ρ=0.2 (weak correlation) and ρ=0.8 (strong correlation) channel estimating performance for the present invention；
Performance compares figure.
Specific embodiment
To keep the features of the present invention and advantage more obvious and easy to understand, the present invention is described in detail with reference to the accompanying drawing.
Fig. 2 is two-way MIMO relay system structural schematic diagram of the invention, two-way MIMO communication system as shown in Figure 2,
Wherein by relaying progress information exchange, M is respectively configured in user 1, user 2 and relaying by user 1 and user 21、M2With N root antenna.
The design assumes that all channels are all quasi-static bulk nanometer materials, and considers time division duplex (TDD) mode.
Embodiment one
Fig. 3 is referred to, Fig. 3 is channel estimating performance figure of the present invention at different channels training sequence number L.System
Parameter are as follows: M1=M2ρ=0=N=2, T=4.Fig. 2 shows from figure 3, it can be seen that for mentioned channel estimation method, channel
H21And H2RNMSE reduce with the increase of signal-to-noise ratio；With the increase of L, channel H21And H2RNMSE also reduce therewith.
Therefore, by increasing channel training number, the performance of proposed channel estimation method can be improved.
Embodiment two
Fig. 4 is referred to, Fig. 4 is channel estimating performance figure of the present invention at different channels training sequence length T.System
Parameter are as follows: M1=M2=N=2, L=5.Fig. 3 shows the increase with T, channel H21And H2RNMSE reduce.Increasing can be passed through
Add the length of channel training sequence, to improve the performance of proposed channel estimation method.
Embodiment three
Fig. 5 is referred to, Fig. 5 is channel estimating performance figure of the present invention at different N.System parameter are as follows: M1=M2=2, L
=T=6.Fig. 4 shows that the channel estimation method of proposition works well in N=2, and in N=3 then almost without playing letter
The left and right of road estimation.This is because F(3)And F(4)The no enough row full rank condition in N=3, mentioned fitting algorithm cannot normal works
Make, mentioned channel estimation method does not play the role of channel estimation at this time.
Embodiment four
Fig. 6 is referred to, Fig. 6 is the present invention in ρ=0.2 (weak correlation) and ρ=0.8 (strong correlation), with existing methods
Channel estimating performance compares figure.System parameter are as follows: M1=M2=2, L=T=6.Fig. 5 shows that Fig. 4 shows to work as H21And H2RQiang Xiang
Guan Shi, channel H21And H2RNMSE obviously increase, even if channel becomes strong correlation, the algorithm proposed also can effectively be estimated
Count channel.
To sum up, the present invention can provide institute in system for the channel estimation of two-way MIMO relay system for each user
Some CSI.The algorithm does not need the pseudoinverse of calculating matrix in each iteration, precision of channel estimation with higher and lower
Computation complexity can quickly and accurately realize channel estimation.
The explanation of above embodiments is only to help to understand method and its main thought of the invention.The content of this specification is not
Interest field of the invention can be limited with this, therefore, protection scope of the present invention should be determined by the appended claims.
Claims (6)
1. the channel joint estimation method of two-way multiple-input and multiple-output relay system, it is characterised in that this method comprises:
The foundation of two-way multiple-input and multiple-output relay system model；
The design of channel training signals；
Relay encodes received signal and is sent to user；
User terminal constructs TUCK-2 tensor model to received signal；
The iterative fitting algorithm of low complex degree is designed to realize the Combined estimator of channel matrix.
2. requiring the channel joint estimation method of the two-way multiple-input and multiple-output relay system according to right 1, feature exists
In: the foundation of the two-way multiple-input and multiple-output relay system model specifically includes:
WithIt respectively indicates user 1 and arrives relay node channel matrix to relay node and user 2,WithRelay node is respectively indicated to user 1 and relay node to the channel matrix of user 2.Design is false
If all channels are all quasi-static bulk nanometer materials, and consider time division duplex (TDD) mode, that is, haveWith
3. requiring the channel joint estimation method of the two-way multiple-input and multiple-output relay system according to right 2, feature exists
In the design of channel training signals, comprising:
During l (l=1 ..., L) height, orthogonal channel training sequenceWithRespectively by user
1 and user 2 be sent to relaying.Wherein orthogonal channel training sequence S(1)And S(2)Meet:
WhereinAnd
The signal that relay node receives are as follows:
WhereinIndicate the relaying noise matrix of first of subprocess.
4. requiring the channel joint estimation method of the two-way multiple-input and multiple-output relay system according to right 3, feature exists
In relay encodes received signal and is sent to user, comprising:
Relaying is to the signal X receivedlIt is encoded, and it is forwarded to user 1 and user 2 respectively.User 1 and user 2 receive
SignalWithIt respectively indicates are as follows:
Wherein,To relay encoder matrix.
5. requiring the channel joint estimation method of the two-way multiple-input and multiple-output relay system according to right 4, feature exists
In user terminal constructs TUCK-2 tensor model to received signal, comprising:
User terminal to receive signal both sides simultaneously multiplied byWithIt obtains
Wherein
It enablesWhereinIt can obtain
Wherein,And
It can be modeled as having noisy TUCK-2 tensor model, the scalar form of the TUCK-2 model is
Whereinf(n1,n2, l) andIt is tensor respectivelyWithTypical element.
According to TUCK-2 resolution characteristic, following three kinds of compact forms can be obtained:
Three compact modelsWith tensorThere is following relationship:
Another compact models can be obtainedIts expression formula is as follows:
6. requiring the channel joint estimation method of the two-way multiple-input and multiple-output relay system according to right 5, feature exists
In designing the iterative fitting algorithm of low complex degree to realize the Combined estimator of channel matrix, comprising:
The design proposes a kind of iterative algorithm of low complex degree to be fitted constructed Tuck-2 model, so that Combined estimator goes out
Channel matrix HiRWithAssuming that F(3)And F(4)For full-row rank, use respectivelyWithIt is rightWithMultiply after progress, can obtain such as
The LS of lower two Kronecker products estimates
Steps are as follows for the fitting algorithm mentioned:
Step (1): two Kronecker products are calculatedWithLS estimation；
Step (2): initializationAnd set it=0；
Step (3): it=it+1；
Step (4): to m=1 ..., M and n2=1 ..., N is calculatedIt is as follows:
Step (5): to mi=1 ..., MiAnd n1=1 ..., N is calculatedIt is as follows:
Step (6): (3) to (5) are repeated until convergence；
Step (7): it is fuzzy to eliminate scale.
In above-mentioned algorithm, it indicates the number of iterations.Since the algorithm does not need the pseudoinverse of calculating matrix in each iteration, because
This is not in convergence problem with lower computation complexity.Under middle high s/n ratio, algorithm reaches changing for convergence needs
In generation, is typically less than the number of 10.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN113381797A (en) * | 2021-05-31 | 2021-09-10 | 北方工业大学 | Unmanned aerial vehicle information monitoring method based on generalized tensor compression |
| CN114172546A (en) * | 2021-12-10 | 2022-03-11 | 中国传媒大学 | Multi-parameter iterative estimation method in RIS auxiliary MIMO system |
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| US20170294946A1 (en) * | 2016-04-11 | 2017-10-12 | National Tsing Hua University | Relay precoder selection method for two-way amplify-and-forward mimo relay systems and communication devices using the selection method or the selected relay precoder |
| CN107786474A (en) * | 2017-11-02 | 2018-03-09 | 中国传媒大学 | A kind of channel estimation methods based on the models of Tucker 2 in MIMO relay system |
| CN108111439A (en) * | 2017-11-02 | 2018-06-01 | 中国传媒大学 | A kind of non-iterative channel estimation methods in two-way MIMO relay system |
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| US20170294946A1 (en) * | 2016-04-11 | 2017-10-12 | National Tsing Hua University | Relay precoder selection method for two-way amplify-and-forward mimo relay systems and communication devices using the selection method or the selected relay precoder |
| US10218418B2 (en) * | 2016-04-11 | 2019-02-26 | National Tsing Hua University | Relay precoder selection method for two-way amplify-and-forward MIMO relay systems and communication devices using the selection method or the selected relay precoder |
| CN107786474A (en) * | 2017-11-02 | 2018-03-09 | 中国传媒大学 | A kind of channel estimation methods based on the models of Tucker 2 in MIMO relay system |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN113381797A (en) * | 2021-05-31 | 2021-09-10 | 北方工业大学 | Unmanned aerial vehicle information monitoring method based on generalized tensor compression |
| CN114172546A (en) * | 2021-12-10 | 2022-03-11 | 中国传媒大学 | Multi-parameter iterative estimation method in RIS auxiliary MIMO system |
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